Identification of potent aldose reductase inhibitors as antidiabetic (Anti-hyperglycemic) agents using QSAR based virtual Screening, molecular Docking, MD simulation and MMGBSA approaches.

The aldose reductase (AR) enzyme is an important target enzyme in the development of therapeutics against hyperglycaemia induced health complications such as retinopathy, etc. In the present study, a quantitative structure activity relationship (QSAR) evaluation of a dataset of 226 reported AR inhibitor (ARi) molecules is performed using a genetic algorithm - multi linear regression (GA-MLR) technique. Multi-criteria decision making (MCDM) analysis furnished two five variables based QSAR models with acceptably high performance reflected in various statistical parameters such as, R2 = 0.79-0.80, Q2 LOO = 0.78-0.79, Q2 LMO = 0.78-0.79. The QSAR model analysis revealed some of the molecular features that play crucial role in deciding inhibitory potency of the molecule against AR such as; hydrophobic Nitrogen within 2 Å of the center of mass of the molecule, non-ring Carbon separated by three and four bonds from hydrogen bond donor atoms, number of sp2 hybridized Oxygen separated by four bonds from sp2 hybridized Carbon atoms, etc. 14 in silico generated hits, using a compound 18 (a most potent ARi from present dataset with pIC50 = 8.04 M) as a template, on QSAR based virtual screening (QSAR-VS) furnished a scaffold 5 with better ARi activity (pIC50 = 8.05 M) than template compound 18. Furthermore, molecular docking of compound 18 (Docking Score = -7.91 kcal/mol) and scaffold 5 (Docking Score = -8.08 kcal/mol) against AR, divulged that they both occupy the specific pocket(s) in AR receptor binding sites through hydrogen bonding and hydrophobic interactions. Molecular dynamic simulation (MDS) and MMGBSA studies right back the docking results by revealing the fact that binding site residues interact with scaffold 5 and compound 18 to produce a stable complex similar to co-crystallized ligand's conformation. The QSAR analysis, molecular docking, and MDS results are all in agreement and complementary. QSAR-VS successfully identified a more potent novel ARi and can be used in the development of therapeutic agents to treat diabetes.

Accuracy of self-reported BMI using objective measurement in high school students.

Self-reported measures for body mass index (BMI) are considered a limitation in research design, especially when they are a primary outcome. Studies have found some populations to be quite accurate when self-reporting BMI; however, there is mixed research on the accuracy of self-reported measurements in adolescents. The aim of this study is to examine the accuracy of self-reported BMI by comparing it with measured BMI in a sample of U.S. adolescents and to understand gender differences. This cross-sectional study collected self-reported height and weight measurements of students from five high schools in four states (Tennessee, South Dakota, Kansas and Florida). Trained researchers took height and weight of students for an objective measurement. BMI was calculated from both sources and categorized (underweight, normal, overweight and obese) using the Centers for Disease Control and Prevention's BMI-for-age percentiles. Participants (n 425; 51⋅0 % female) had a mean age of 16⋅3 years old, and the majority were White (47⋅5 %). Limits of agreement (LOA) analysis revealed that BMI and weight were underreported, and height was overreported in the overall sample, in females, and in males. LOA analysis was fair for BMI in all three groups. Overall agreement in BMI categorisation was considered substantial (Κ 0⋅71, P < 0⋅001). As BMI increased, more height and weight inaccuracies led to decreased accuracy in BMI categorisation, and the specificity of obese participants was low (50⋅0 %). This study's findings suggest that using self-reported values to categorize BMI is more accurate than using continuous BMI values when self-reported measures are used in health-related interventions.

Enumeration of circulating fibrocytes for clinical use in asthma by an optimized single-platform flow cytometry assay.

BACKGROUND: Elevated numbers of circulating fibrocytes are associated with inadequately controlled asthma, poor response to available therapies, and increased risk of adverse outcomes. The lack of reliable and clinically-applicable assays precludes a proper evaluation of blood fibrocyte count as a prognostic biomarker in asthma. This report concerns the use of a multiparameter flow cytometry assay for the enumeration of fibrocytes in the whole blood. METHODS: Consenting fibrocyte donors were 19 patients with asthma well controlled by current treatment, 16 patients with treatment-resistant asthma, 9 patients with transiently uncontrolled asthma and 14 age-matched normal individuals. Blood sampling was performed once in patients with transiently uncontrolled asthma and twice, at an interval of one week, in the other subjects. The assay was performed in 100 µl of whole blood and involved a sequential gating strategy and absolute fibrocyte counting with a single instrument (single-platform assay). RESULTS: The quantification of circulating fibrocytes by this assay was analytically and clinically valid. In individuals with stable clinical conditions, the repeatability of blood fibrocyte counts over one week was good. The intraclass correlation coefficient was 0.939 and 96.88% of the total variability reflected on-average differences among the tested subjects. Stabilized blood samples could be stored at 4 °C for up to 96 h before processing. CONCLUSIONS: The novel assay for the enumeration of fibrocytes in the whole blood is reliable and clinically applicable. GENERAL SIGNIFICANCE: This report demonstrates the validity and reliability of the first optimized assay for the enumeration of circulating fibrocytes in multicenter clinical trials.